Intravoxel Incoherent Motion Diffusion-Weighted MR Imaging Findings of Infrapatellar Fat Pad Signal Abnormalities: Comparison Between Symptomatic and Asymptomatic Knee Osteoarthritis
Bibliographic record
Abstract
RATIONALE AND OBJECTIVES: Infrapatellar fat pad (IPFP) proton density-weighted images (PdWI) hyperintense regions on MRI are an important imaging feature of knee osteoarthritis (KOA) and are thought to represent inflammation which may induce knee pain. The aim of the study was to compare the intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) findings of PdWI hyperintense regions of IPFP between symptomatic and asymptomatic KOA and to determine whether IVIM-DWI parameters can be used as an objective biomarker for symptomatic KOA. MATERIALS AND METHODS: In total, 84 patients with symptomatic KOA, 43 asymptomatic KOA persons, and 30 healthy controls with MRI were retrospectively reviewed. Demographic, IPFP-synovitis, Western Ontario and McMaster Osteoarthritis Index (WOMAC) pain sub-score, IPFP volume and depth and quantitative parameters of IVIM-DWI were collected. The chi-square test, Binary logistic regression and receiver operating characteristic curve (ROC) analysis were used for diagnostic performance comparison. RESULTS: The IPFP volume and depth were statistically significant differences between the non-KOA and sKOA groups (p<0.05). The IPFP PdWI hyperintense regions demonstrated significantly higher values of D and D* in the symptomatic KOA compared to those in the asymptomatic KOA (1.51±0.47 vs. 1.73±0.40 for D and 19.24±6.44 vs. 27.09±9.75 for D*) (both p<0.05). Multivariate logistic regression analyses showed that Higher D and D* values of IPFP hyperintense region were significantly associated with higher risks of knee pain (OR: 1.97; 95% CI: 1.21-3.19; p=0.006 for D and OR: 1.24; 95% CI: 1.09-1.41; p=0.001 for D*). Sensitivity and specificity of D value for symptomatic KOA were 80.28% and 83.33%, with an AUC of 0.78 (0.68-0.86). D* value had the sensitivity with 92.96% and a specificity of 58.33%, with an AUC of 0.82 (0.73-0.89) for symptomatic KOA. CONCLUSION: IVIM-DWI can be used as an additional functional imaging technique to study IPFP with signal abnormalities on PdWI, and the D and D* values may have potential value to predict the symptom in mild-to-moderate KOA patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".